Update app.py

app.py

@@ -64,24 +64,11 @@ def predict(input_image):
     result = {key: result[key] for key in result if result[key] > 0.5}
     return result
 
-
-
-
-'''    
-    image_processor = AutoImageProcessor.from_pretrained(checkpoint_name)
-    # predict
-    inputs = image_processor(input_image, return_tensors="pt")
-    image = np.expand_dims(inputs, axis=0)
-    pred = model.predict(image, verbose=0)
-    pred = pred[0]
-    confidences = {classes_names[i]: round(float(pred[i]), 2) for i in range(50)}
-    return confidences
-'''
-
 gr.Interface(
     fn=predict,
     inputs=gr.Image(shape=(224, 224)),
-    outputs=gr.Label(num_top_classes=5),
+    #outputs=gr.Label(num_top_classes=5),
+    outputs="label",
     examples=[
         "Dalbergia oliveri.JPG",
         "Eucalyptus.JPG",